The Automatic Verification of Image-Text Claims (AVerImaTeC) Shared Task
This is an incremental effort to improve verification systems for image-text claims, addressing the problem of misinformation detection for researchers and practitioners in AI and media analysis.
The AVerImaTeC shared task tackled the problem of verifying real-world image-text claims by advancing system development for evidence retrieval and verification, with the winning team achieving an AVerImaTeC score of 0.5455 and all systems outperforming the baseline.
The Automatic Verification of Image-Text Claims (AVerImaTeC) shared task aims to advance system development for retrieving evidence and verifying real-world image-text claims. Participants were allowed to either employ external knowledge sources, such as web search engines, or leverage the curated knowledge store provided by the organizers. System performance was evaluated using the AVerImaTeC score, defined as a conditional verdict accuracy in which a verdict is considered correct only when the associated evidence score exceeds a predefined threshold. The shared task attracted 14 submissions during the development phase and 6 submissions during the testing phase. All participating systems in the testing phase outperformed the baseline provided. The winning team, HUMANE, achieved an AVerImaTeC score of 0.5455. This paper provides a detailed description of the shared task, presents the complete evaluation results, and discusses key insights and lessons learned.